The course content addresses the following topics:
- The history of sampling practice and research
- Data quality objectives
- ISO standards
- Sampling dimensions of the lot
- Representative sampling and proportional sampling
- Theory of sampling and definitions
- Variography and process control
- Pierre Gy and sampling errors
- Sampling in the mining value chain
- Descriptive statistics
- Accuracy, precision, error, and bias
- Components of bias and bias testing
- Understanding error and bias
- Sampling of slurries
- Survey of mass reduction techniques
- Replication experiment
- Characterising heterogeneity (duplicate sample analysis, segregation free analysis)
- Compiling the calibration curves
- Compiling the sampling nomogram
- Uses of the sampling nomogram